Appreciative inquiry and lean strategy in global management contexts

Appreciative Inquiry: Focusing on the Positive

According to Bushe's (2011) article, appreciative inquiry (AI) is a method of inquiry in leadership that focuses on what works as opposed to what does not work (Stavros, Cooperrider, and Kelly, 2003). This is a method that fits in well with the lean strategy initiated by Japanese leaders; what is unnecessary is completely discarded in favor of a focus on perpetuating the strategies and elements that do work. As such, Bushe's article describes four components within the strategy: Discovery, Dream, Design, and Delivery. During the Discovery stage, the focus is on discovering what is best regarding a specific strategy or focus point within the business. The Dream stage entails participants focusing on a mental image of the company or group at its best. The result is usually a graphical representation of this concept. In Design, participants use the concept created during Dream to devise specific strategies to reach the ideal state, while delivery entails the outcomes of the effort.

There are many ways in which the theory can be applied to specific management situations. The Japanese focus on lean, for example, can gain considerably from a philosophy that focuses on the elements of accomplishing goals rather than those elements that should be discarded. AI focuses precisely on what is positive, what works, and what is likely to work in the future. It is a core principle that runs parallel with lean management. While the strategy was initiated in the United States, it is applicable across the globe, with authors such as Robertsen (2010) focusing their research efforts on the Danish context.

The value of Bushe's article is significant for a number of reasons. First, it provides significant new information about a theory that has been in existence for decades. There is, for example, a lack of consensus on the specific ways in which the various components of AI should be implemented. Particularly, the "Delivery" component has been subject to significant disagreement and divergence when it comes to the ways in which different companies implement it. The article therefore provides somewhat needed clarification on the finer points of AI and further develops components that have proven to need it. Another reason for the high value of this article to the field of study is its applicability to the wider context; regardless of country or culture, AI can integrate with the existing culture or philosophy. One can, for example, safely assume that the main goal for any business is to be the best it can be (Hammond, n.d.). Finally, the article's value lies in the fact that it builds on previous work by authors such as Bushe (2005) and others.

The global implications of AI are that it can be applied to any business context and any leadership style. This makes it a significantly useful business strategy throughout the world, as mentioned above. Regardless of culture or leadership style, it can be assumed that all companies are focused on their own survival and the best ways in which to accomplish their own longevity. AI is sufficiently flexible to accommodate any company with this requirement, regardless of other differentiating factors. In the Japanese context, then, the strategy would focus on the efficiency level of existing business strategies and on increasing this level of efficiency. Other cultures would focus on values that are important to them and their way of doing business.